Dataset Information

Effect of Calcium Stearate in the Mechanical and Physical Properties of Concrete with PCC and Fly Ash as Binders.

ABSTRACT: This work aims to study the effect of Ca(C18H35O2)2 (calcium stearate) on the properties of concrete by using Portland composite cement (PCC) and fly ash as binders. The calcium stearate content used in the concrete here consists of 0, 1, 5, and 10 kg per m3 of concrete volume, or alternatively, 0 to 2.85% by the weight of cement. We have performed several tests for each of the contents, namely, compressive strength, water absorption, chloride ion infiltration, and accelerated corrosion tests. According to the testing, we have found that with the addition of calcium stearate at 1 kg/m3 in self-compacting concrete (SCC) with 10% fly ash, the mechanical and physical properties of SCC can be improved significantly when compared to the SCC without fly ash and calcium stearate, resulting in a stable compressive strength, lower water absorption, lower chloride ion infiltration, and lower degree of corrosion attack.

SUBMITTER: Maryoto A

PROVIDER: S-EPMC7143480 | biostudies-literature | 2020 Mar

REPOSITORIES: biostudies-literature

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Publications

Effect of Calcium Stearate in the Mechanical and Physical Properties of Concrete with PCC and Fly Ash as Binders.

Maryoto Agus A Sthenly Gan Buntara B Intang Setyo Hermanto Nor N Setijadi Rachmad R

Materials (Basel, Switzerland) 20200319 6

This work aims to study the effect of Ca(C18H35O2)2 (calcium stearate) on the properties of concrete by using Portland composite cement (PCC) and fly ash as binders. The calcium stearate content used in the concrete here consists of 0, 1, 5, and 10 kg per m3 of concrete volume, or alternatively, 0 to 2.85% by the weight of cement. We have performed several tests for each of the contents, namely, compressive strength, water absorption, chlori ...[more]

PMID: 32204406

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Project description:The emission of greenhouse gases and natural-resource depletion caused by the production of ordinary Portland cement (OPC) have a detrimental effect on the environment. Thus, an alternative means is required to produce eco-friendly concrete such as geopolymer concrete (GPC). However, GPC has a complex cementitious matrix and an ambiguous mix design. Aside from that, the composition and proportions of materials utilized may have an impact on the compressive strength. Similarly, the use of robust and efficient machine-learning (ML) approaches is now required to forecast the strength of such a composite cementitious matrix. As a result, this study anticipated the compressive strength of GPC with waste resources using ensemble and non-ensemble ML algorithms. This was accomplished through the use of Anaconda (Python). To build a strong ensemble learner by integrating weak learners, adaptive boosting, random forest (RF), and ensemble learner bagging were employed. Furthermore, ensemble learners were utilized on non-ensemble or weak learners, such as decision trees (DT) and support vector machines (SVM) via regression. The data encompassed 156 statistical samples in which nine variables, namely superplasticizer (kg/m3), fly ash (kg/m3), ground granulated blast-furnace slag (GGBS), temperature (°C), coarse and fine aggregate (kg/m3), sodium silicate (Na2SiO3), and sodium hydroxide (NaOH), were chosen to anticipate the results. Exploring it in depth, twenty sub-models with ensemble boosting and bagging approaches were trained, and tuning was performed to achieve the highest possible coefficient of determination (R2). Moreover, cross K-Fold validation analysis and statistical checks were performed via indicators for the evaluation of the models. The result revealed that ensemble approaches yielded robust performance compared to non-ensemble algorithms. Generally, an ensemble learner with the RF and bagging approach on a DT yielded robust performance by achieving a better R2 as 0.93, and with the lowest statistical errors. The communal model in artificial-intelligence analysis, on average, improved the accuracy of the model.

Dataset Information

Effect of Calcium Stearate in the Mechanical and Physical Properties of Concrete with PCC and Fly Ash as Binders.

Publications

Effect of Calcium Stearate in the Mechanical and Physical Properties of Concrete with PCC and Fly Ash as Binders.

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